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Rami FZ, Li L, Le TH, Kang C, Han MA, Chung YC. Risk and protective factors for severe mental disorders in Asia. Neurosci Biobehav Rev 2024; 161:105652. [PMID: 38608827 DOI: 10.1016/j.neubiorev.2024.105652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 03/22/2024] [Accepted: 04/03/2024] [Indexed: 04/14/2024]
Abstract
Among 369 diseases and injuries, the years lived with disability (YLDs) and disability-adjusted life-years (DALYs) rates for severe mental illnesses (SMIs) are within the top 20 %. Research on risk and protective factors for SMIs is critically important, as acting on modifiable factors may reduce their incidence or postpone their onset, while early detection of new cases enables prompt treatment and improves prognosis. However, as most of the studies on these factors are from Western countries, the findings are not generalizable across ethnic groups. This led us to conduct a systematic review of the risk and protective factors for SMIs identified in Asian studies. There were common factors in Asian and Western studies and unique factors in Asian studies. In-depth knowledge of these factors could help reduce disability, and the economic and emotional burden of SMIs. We hope that this review will inform future research and policy-making on mental health in Asian countries.
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Affiliation(s)
- Fatima Zahra Rami
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Ling Li
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Thi Hung Le
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Chaeyeong Kang
- Research Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea
| | - Mi Ah Han
- Department of Preventive Medicine, College of Medicine, Chosun University, Republic of Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju, Republic of Korea; Research Institute of Clinical Medicine of Jeonbuk National University and Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Republic of Korea.
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Tan SMX, Yee JY, Budhraja S, Singh B, Doborjeh Z, Doborjeh M, Kasabov N, Lai E, Sumich A, Lee J, Goh WWB. RNA-sequencing of peripheral whole blood of individuals at ultra-high-risk for psychosis - A longitudinal perspective. Asian J Psychiatr 2023; 89:103796. [PMID: 37837946 DOI: 10.1016/j.ajp.2023.103796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/31/2023] [Accepted: 09/30/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND The peripheral blood is an attractive source of prognostic biomarkers for psychosis conversion. There is limited research on the transcriptomic changes associated with psychosis conversion in the peripheral whole blood. STUDY DESIGN We performed RNA-sequencing of peripheral whole blood from 65 ultra-high-risk (UHR) participants and 70 healthy control participants recruited in the Longitudinal Youth-at-Risk Study (LYRIKS) cohort. 13 UHR participants converted in the study duration. Samples were collected at 3 timepoints, at 12-months interval across a 2-year period. We examined whether the genes differential with psychosis conversion contain schizophrenia risk loci. We then examined the functional ontologies and GWAS associations of the differential genes. We also identified the overlap between differentially expressed genes across different comparisons. STUDY RESULTS Genes containing schizophrenia risk loci were not differentially expressed in the peripheral whole blood in psychosis conversion. The differentially expressed genes in psychosis conversion are enriched for ontologies associated with cellular replication. The differentially expressed genes in psychosis conversion are associated with non-neurological GWAS phenotypes reported to be perturbed in schizophrenia and psychosis but not schizophrenia and psychosis phenotypes themselves. We found minimal overlap between the genes differential with psychosis conversion and the genes that are differential between pre-conversion and non-conversion samples. CONCLUSION The associations between psychosis conversion and peripheral blood-based biomarkers are likely to be indirect. Further studies to elucidate the mechanism behind potential indirect associations are needed.
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Affiliation(s)
- Samuel Ming Xuan Tan
- School of Biological Sciences, Nanyang Technological University, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Center for Biomedical Informatics, Nanyang Technological University, Singapore
| | - Jie Yin Yee
- Research Division, Institute of Mental Health, Singapore
| | - Sugam Budhraja
- Knowledge Engineering and Discovery Research Innovation, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, New Zealand
| | - Balkaran Singh
- Knowledge Engineering and Discovery Research Innovation, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, New Zealand
| | - Zohreh Doborjeh
- School of Population Health, The University of Auckland, New Zealand
| | - Maryam Doborjeh
- Knowledge Engineering and Discovery Research Innovation, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, New Zealand
| | - Nikola Kasabov
- Knowledge Engineering and Discovery Research Innovation, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, New Zealand
| | - Edmund Lai
- Knowledge Engineering and Discovery Research Innovation, School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, New Zealand
| | | | - Jimmy Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Research Division, Institute of Mental Health, Singapore
| | - Wilson Wen Bin Goh
- School of Biological Sciences, Nanyang Technological University, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Center for Biomedical Informatics, Nanyang Technological University, Singapore.
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Budhraja S, Doborjeh M, Singh B, Tan S, Doborjeh Z, Lai E, Merkin A, Lee J, Goh W, Kasabov N. Filter and Wrapper Stacking Ensemble (FWSE): a robust approach for reliable biomarker discovery in high-dimensional omics data. Brief Bioinform 2023; 24:bbad382. [PMID: 37889118 PMCID: PMC10605029 DOI: 10.1093/bib/bbad382] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 09/18/2023] [Accepted: 10/03/2023] [Indexed: 10/28/2023] Open
Abstract
Selecting informative features, such as accurate biomarkers for disease diagnosis, prognosis and response to treatment, is an essential task in the field of bioinformatics. Medical data often contain thousands of features and identifying potential biomarkers is challenging due to small number of samples in the data, method dependence and non-reproducibility. This paper proposes a novel ensemble feature selection method, named Filter and Wrapper Stacking Ensemble (FWSE), to identify reproducible biomarkers from high-dimensional omics data. In FWSE, filter feature selection methods are run on numerous subsets of the data to eliminate irrelevant features, and then wrapper feature selection methods are applied to rank the top features. The method was validated on four high-dimensional medical datasets related to mental illnesses and cancer. The results indicate that the features selected by FWSE are stable and statistically more significant than the ones obtained by existing methods while also demonstrating biological relevance. Furthermore, FWSE is a generic method, applicable to various high-dimensional datasets in the fields of machine intelligence and bioinformatics.
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Affiliation(s)
- Sugam Budhraja
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, 55 Wellesley Street East, 1010 Auckland, New Zealand
| | - Maryam Doborjeh
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, 55 Wellesley Street East, 1010 Auckland, New Zealand
| | - Balkaran Singh
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, 55 Wellesley Street East, 1010 Auckland, New Zealand
| | - Samuel Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore
| | - Zohreh Doborjeh
- School of Population Health, The University of Auckland, Grafton, 1023,Auckland, New Zealand
| | - Edmund Lai
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, 55 Wellesley Street East, 1010 Auckland, New Zealand
| | - Alexander Merkin
- National Institute for Stroke and Applied Neuroscience, Auckland University of Technology, 55 Wellesley Street East, 1010 Auckland, New Zealand
| | - Jimmy Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore
- Institute of Mental Health, 10 Buangkok View, 539747, Singapore
| | - Wilson Goh
- Lee Kong Chian School of Medicine, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore
- Center for Biomedical Informatics, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore
- School of Biological Sciences, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore
| | - Nikola Kasabov
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, 55 Wellesley Street East, 1010 Auckland, New Zealand
- Intelligent Systems Research Center, Ulster University, Magee Campus, Derry, BT48 7JL, Ulster, United Kingdom
- Auckland Bioengineering Institute, The University of Auckland, 6/70 Symonds Street, 1010 Auckland, New Zealand
- Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria
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Singh B, Doborjeh M, Doborjeh Z, Budhraja S, Tan S, Sumich A, Goh W, Lee J, Lai E, Kasabov N. Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data. Sci Rep 2023; 13:456. [PMID: 36624117 PMCID: PMC9829920 DOI: 10.1038/s41598-022-27132-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/26/2022] [Indexed: 01/11/2023] Open
Abstract
Interpretable machine learning models for gene expression datasets are important for understanding the decision-making process of a classifier and gaining insights on the underlying molecular processes of genetic conditions. Interpretable models can potentially support early diagnosis before full disease manifestation. This is particularly important yet, challenging for mental health. We hypothesise this is due to extreme heterogeneity issues which may be overcome and explained by personalised modelling techniques. Thus far, most machine learning methods applied to gene expression datasets, including deep neural networks, lack personalised interpretability. This paper proposes a new methodology named personalised constrained neuro fuzzy inference (PCNFI) for learning personalised rules from high dimensional datasets which are structurally and semantically interpretable. Case studies on two mental health related datasets (schizophrenia and bipolar disorders) have shown that the relatively short and simple personalised fuzzy rules provided enhanced interpretability as well as better classification performance compared to other commonly used machine learning methods. Performance test on a cancer dataset also showed that PCNFI matches previous benchmarks. Insights from our approach also indicated the importance of two genes (ATRX and TSPAN2) as possible biomarkers for early differentiation of ultra-high risk, bipolar and healthy individuals. These genes are linked to cognitive ability and impulsive behaviour. Our findings suggest a significant starting point for further research into the biological role of cognitive and impulsivity-related differences. With potential applications across bio-medical research, the proposed PCNFI method is promising for diagnosis, prognosis, and the design of personalised treatment plans for better outcomes in the future.
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Affiliation(s)
- Balkaran Singh
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
| | - Maryam Doborjeh
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand.
| | - Zohreh Doborjeh
- School of Population Health, The University of Auckland, Auckland, New Zealand
- School of Psychology, The University of Waikato, Hamilton, New Zealand
| | - Sugam Budhraja
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
| | - Samuel Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Singapore, Singapore
| | - Alexander Sumich
- Department of Psychology, Nottingham Trent University, Nottingham, UK
| | - Wilson Goh
- Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Singapore, Singapore
- Center for Biomedical Informatics, Nanyang Technological University (NTU), Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University (NTU), Singapore, Singapore
| | - Jimmy Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Singapore, Singapore
- Institute for Mental Health, Singapore, Singapore
| | - Edmund Lai
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
| | - Nikola Kasabov
- Knowledge Engineering and Discovery Research Innovation (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
- Intelligent Systems Research Center, Ulster University, Derry, UK
- Institute for Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria
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Oliver D, Arribas M, Radua J, Salazar de Pablo G, De Micheli A, Spada G, Mensi MM, Kotlicka-Antczak M, Borgatti R, Solmi M, Shin JI, Woods SW, Addington J, McGuire P, Fusar-Poli P. Prognostic accuracy and clinical utility of psychometric instruments for individuals at clinical high-risk of psychosis: a systematic review and meta-analysis. Mol Psychiatry 2022; 27:3670-3678. [PMID: 35665763 PMCID: PMC9708585 DOI: 10.1038/s41380-022-01611-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/21/2022] [Accepted: 04/28/2022] [Indexed: 02/08/2023]
Abstract
Accurate prognostication of individuals at clinical high-risk for psychosis (CHR-P) is an essential initial step for effective primary indicated prevention. We aimed to summarise the prognostic accuracy and clinical utility of CHR-P assessments for primary indicated psychosis prevention. Web of Knowledge databases were searched until 1st January 2022 for longitudinal studies following-up individuals undergoing a psychometric or diagnostic CHR-P assessment, reporting transition to psychotic disorders in both those who meet CHR-P criteria (CHR-P + ) or not (CHR-P-). Prognostic accuracy meta-analysis was conducted following relevant guidelines. Primary outcome was prognostic accuracy, indexed by area-under-the-curve (AUC), sensitivity and specificity, estimated by the number of true positives, false positives, false negatives and true negatives at the longest available follow-up time. Clinical utility analyses included: likelihood ratios, Fagan's nomogram, and population-level preventive capacity (Population Attributable Fraction, PAF). A total of 22 studies (n = 4 966, 47.5% female, age range 12-40) were included. There were not enough meta-analysable studies on CHR-P diagnostic criteria (DSM-5 Attenuated Psychosis Syndrome) or non-clinical samples. Prognostic accuracy of CHR-P psychometric instruments in clinical samples (individuals referred to CHR-P services or diagnosed with 22q.11.2 deletion syndrome) was excellent: AUC = 0.85 (95% CI: 0.81-0.88) at a mean follow-up time of 34 months. This result was driven by outstanding sensitivity (0.93, 95% CI: 0.87-0.96) and poor specificity (0.58, 95% CI: 0.50-0.66). Being CHR-P + was associated with a small likelihood ratio LR + (2.17, 95% CI: 1.81-2.60) for developing psychosis. Being CHR-P- was associated with a large LR- (0.11, 95%CI: 0.06-0.21) for developing psychosis. Fagan's nomogram indicated a low positive (0.0017%) and negative (0.0001%) post-test risk in non-clinical general population samples. The PAF of the CHR-P state is 10.9% (95% CI: 4.1-25.5%). These findings consolidate the use of psychometric instruments for CHR-P in clinical samples for primary indicated prevention of psychosis. Future research should improve the ability to rule in psychosis risk.
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Affiliation(s)
- Dominic Oliver
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Maite Arribas
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Joaquim Radua
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute, Stockholm, Sweden
| | - Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Child and Adolescent Mental Health Services, South London & Maudsley NHS Trust, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrea De Micheli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, UK
| | - Giulia Spada
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Martina Maria Mensi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- IRCCS Mondino Foundation, Childhood and Adolescent Neuropsychiatry Unit, Pavia, Italy
| | - Magdalena Kotlicka-Antczak
- Early Psychosis Diagnosis and Treatment Lab, Department of Affective and Psychotic Disorders, Medical University of Lodz, Lodz, Poland
| | - Renato Borgatti
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- IRCCS Mondino Foundation, Childhood and Adolescent Neuropsychiatry Unit, Pavia, Italy
| | - Marco Solmi
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada
- Department of Mental Health, The Ottawa Hospital, Ottawa, ON, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute (OHRI), University of Ottawa, Ottawa, ON, Canada
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Jean Addington
- Department of Psychiatry, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Philip McGuire
- OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, UK
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Yee JY, Chow SQ, Lim K, Goh W, Sng J, Lee T, Lee J. Haptoglobin in ultra-high risk of psychosis – Findings from the longitudinal youth at risk study (LYRIKS). Brain Behav Immun Health 2022; 23:100481. [PMID: 35757657 PMCID: PMC9214821 DOI: 10.1016/j.bbih.2022.100481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 05/24/2022] [Accepted: 06/04/2022] [Indexed: 11/21/2022] Open
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Zhang X, Lee J, Goh WWB. An Investigation of How Normalisation and Local Modelling Techniques Confound Machine Learning Performance In a Mental Health Study. Heliyon 2022; 8:e09502. [PMID: 35663731 PMCID: PMC9156999 DOI: 10.1016/j.heliyon.2022.e09502] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/12/2022] [Accepted: 05/16/2022] [Indexed: 01/12/2023] Open
Abstract
Machine learning (ML) is increasingly deployed on biomedical studies for biomarker development (feature selection) and diagnostic/prognostic technologies (classification). While different ML techniques produce different feature sets and classification performances, less understood is how upstream data processing methods (e.g., normalisation) impact downstream analyses. Using a clinical mental health dataset, we investigated the impact of different normalisation techniques on classification model performance. Gene Fuzzy Scoring (GFS), an in-house developed normalisation technique, is compared against widely used normalisation methods such as global quantile normalisation, class-specific quantile normalisation and surrogate variable analysis. We report that choice of normalisation technique has strong influence on feature selection. with GFS outperforming other techniques. Although GFS parameters are tuneable, good classification model performance (ROC-AUC > 0.90) is observed regardless of the GFS parameter settings. We also contrasted our results against local modelling, which is meant to improve the resolution and meaningfulness of classification models built on heterogeneous data. Local models, when derived from non-biologically meaningful subpopulations, perform worse than global models. A deep dive however, revealed that the factors driving cluster formation has little to do with the phenotype-of-interest. This finding is critical, as local models are often seen as a superior means of clinical data modelling. We advise against such naivete. Additionally, we have developed a combinatorial reasoning approach using both global and local paradigms: This helped reveal potential data quality issues or underlying factors causing data heterogeneity that are often overlooked. It also assists to explain the model as well as provides directions for further improvement.
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Affiliation(s)
- Xinxin Zhang
- School of Biological Sciences, Nanyang Technological University, 637551, Singapore
| | - Jimmy Lee
- North Region & Department of Psychosis, Institute of Mental Health, 539747, Singapore
- Corresponding author.
| | - Wilson Wen Bin Goh
- School of Biological Sciences, Nanyang Technological University, 637551, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, 636921, Singapore
- Centre for Biomedical Informatics, Nanyang Technological University, 636921, Singapore
- Corresponding author.
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8
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Lim K, Rapisarda A, Keefe RSE, Lee J. Social skills, negative symptoms and real-world functioning in individuals at ultra-high risk of psychosis. Asian J Psychiatr 2022; 69:102996. [PMID: 35026654 DOI: 10.1016/j.ajp.2021.102996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/28/2021] [Accepted: 12/27/2021] [Indexed: 11/02/2022]
Abstract
BACKGROUND Impairment in real-world social functioning is observed in individuals at Ultra-High Risk (UHR) of psychosis. Both social skills and negative symptoms appear to influence real-world functioning. This study aims to examine the psychometric properties of a social skills measure, the High-Risk Social Challenge task (HiSoC), and evaluate the relationship between social skills, negative symptoms, and real-world functioning in UHR individuals. METHODS HiSoC data was analysed in 87 UHR individuals and 358 healthy controls. Exploratory factor analysis (EFA) was used to evaluate the factor structure of the HiSoC task. Convergent and divergent validity were assessed. Negative symptoms were assessed on the Positive and Negative Syndrome Scale (PANSS) and real-world functioning was indexed by the Global Assessment of Functioning (GAF). Commonality analysis was used to partition unique and shared variance of HiSoC and negative symptoms with real-world functioning. RESULTS EFA yielded a three-factor structure of HiSoC consisting of Affect, Odd behaviour and language, and Social-interpersonal. The HiSoC task discriminated UHR and healthy controls (p < 0.001, Cohen's d = 0.437-0.598). Commonality analysis revealed that the unique variance of the social amotivation subdomain of negative symptoms was the strongest predictor of GAF (p < .001, R2 = .480). Shared variance of 3.7% between HiSoC Social-interpersonal and social amotivation was observed in relation to functioning. CONCLUSION The HiSoC is a psychometrically valid task that is sensitive to identify social skill deficits in UHR. While social skills are related to functioning, experiential negative symptoms appear to be an important target for improving real-world functional outcomes.
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Affiliation(s)
- Keane Lim
- Research Division, Institute of Mental Health, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health, Singapore; Neuroscience and Behavioural Disorders, Duke-NUS Medical School, Singapore
| | - Richard S E Keefe
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, United States
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore; Department of Psychosis, Institute of Mental Health, Singapore; Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
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Lim K, Peh OH, Yang Z, Rekhi G, Rapisarda A, See YM, Rashid NAA, Ang MS, Lee SA, Sim K, Huang H, Lencz T, Lee J, Lam M. Large-scale evaluation of the Positive and Negative Syndrome Scale (PANSS) symptom architecture in schizophrenia. Asian J Psychiatr 2021; 62:102732. [PMID: 34118560 DOI: 10.1016/j.ajp.2021.102732] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 05/25/2021] [Accepted: 05/28/2021] [Indexed: 11/17/2022]
Abstract
Although the Positive and Negative Syndrome Scale (PANSS) is widely utilized in schizophrenia research, variability in specific item loading exist, hindering reproducibility and generalizability of findings across schizophrenia samples. We aim to establish a common PANSS factor structure from a large multi-ethnic sample and validate it against a meta-analysis of existing PANSS models. Schizophrenia participants (N = 3511) included in the current study were part of the Singapore Translational and Clinical Research Program (STCRP) and the Clinical Antipsychotic Trials for Intervention Effectiveness (CATIE). Exploratory Factor Analysis (EFA) was conducted to identify the factor structure of PANSS and validated with a meta-analysis (N = 16,171) of existing PANSS models. Temporal stability of the PANSS model and generalizability to individuals at ultra-high risk (UHR) of psychosis were evaluated. A five-factor solution best fit the PANSS data. These were the i) Positive, ii) Negative, iii) Cognitive/disorganization, iv) Depression/anxiety and v) Hostility factors. Convergence of PANSS symptom architecture between EFA model and meta-analysis was observed. Modest longitudinal reliability was observed. The schizophrenia derived PANSS factor model fit the UHR population, but not vice versa. We found that two other domains, Social Amotivation (SA) and Diminished Expression (DE), were nested within the negative symptoms factor. Here, we report one of the largest transethnic factorial structures of PANSS symptom domains (N = 19,682). Evidence reported here serves as crucial consolidation of a common PANSS structure that could aid in furthering our understanding of schizophrenia.
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Affiliation(s)
- Keane Lim
- Research Division, Institute of Mental Health, Singapore
| | - Oon-Him Peh
- Research Division, Institute of Mental Health, Singapore
| | - Zixu Yang
- Research Division, Institute of Mental Health, Singapore
| | - Gurpreet Rekhi
- Research Division, Institute of Mental Health, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health, Singapore; Duke-NUS Medical School, Singapore
| | - Yuen-Mei See
- Research Division, Institute of Mental Health, Singapore
| | | | - Mei-San Ang
- Research Division, Institute of Mental Health, Singapore
| | - Sara-Ann Lee
- Research Division, Institute of Mental Health, Singapore
| | - Kang Sim
- Research Division, Institute of Mental Health, Singapore
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Todd Lencz
- Feinstein Institute of Medical Research, The Zucker Hillside Hospital, New York, United States
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore; Department of Psychosis, Institute of Mental Health, Singapore; Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore; Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, United States; Feinstein Institute of Medical Research, The Zucker Hillside Hospital, New York, United States.
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10
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Raballo A, Poletti M, Preti A. Negative Prognostic Effect of Baseline Antipsychotic Exposure in Clinical High Risk for Psychosis (CHR-P): Is Pre-Test Risk Enrichment the Hidden Culprit? Int J Neuropsychopharmacol 2021; 24:710-720. [PMID: 34036323 PMCID: PMC8453273 DOI: 10.1093/ijnp/pyab030] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/19/2021] [Accepted: 05/21/2021] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION Sample enrichment is a key factor in contemporary early-detection strategies aimed at the identification of help-seekers at increased risk of imminent transition to psychosis. We undertook a meta-analytic investigation to ascertain the role of sample enrichment in the recently highlighted negative prognostic effect of baseline antipsychotic (AP) exposure in clinical high-risk (CHR-P) of psychosis individuals. METHODS Systematic review and meta-analysis of all published studies on CHR-P were identified according to a validated diagnostic procedure. The outcome was the proportion of transition to psychosis, which was calculated according to the Freeman-Tukey double arcsine transformation. RESULTS Thirty-three eligible studies were identified, including 16 samples with details on AP exposure at baseline and 17 samples with baseline AP exposure as exclusion criterion for enrollment. Those with baseline exposure to AP (n = 395) had higher transition rates (29.9%; 95% CI: 25.1%-34.8%) than those without baseline exposure to AP in the same study (n = 1289; 17.2%; 15.1%-19.4%) and those coming from samples that did not include people who were exposed to AP at baseline (n = 2073; 16.2%; 14.6%-17.8%; P < .05 in both the fixed-effects and the random-effects models). Heterogeneity within studies was substantial, with values above 75% in all comparisons. CONCLUSIONS Sample enrichment is not a plausible explanation for the higher risk of transition to psychosis of CHR-P individuals who were already exposed to AP at the enrollment in specialized early-detection programs. Baseline exposure to AP at CHR-P assessment is a major index of enhanced, imminent risk of psychosis.
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Affiliation(s)
- Andrea Raballo
- Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia, Perugia, Italy,Center for Translational, Phenomenological and Developmental Psychopathology (CTPDP), Perugia University Hospital, Perugia, Italy,Correspondence: Andrea Raballo, MD, PhD, Section of Psychiatry, Clinical Psychology and Rehabilitation, Department of Medicine, University of Perugia Piazzale Lucio Severi 1, 06132, Perugia, Italy ()
| | - Michele Poletti
- Department of Mental Health and Pathological Addiction, Child and Adolescent Neuropsychiatry Service, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | - Antonio Preti
- Department of Neuroscience, University of Turin, Turin, Italy
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11
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Salazar de Pablo G, Estradé A, Cutroni M, Andlauer O, Fusar-Poli P. Establishing a clinical service to prevent psychosis: What, how and when? Systematic review. Transl Psychiatry 2021; 11:43. [PMID: 33441556 PMCID: PMC7807021 DOI: 10.1038/s41398-020-01165-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 11/27/2020] [Accepted: 12/03/2020] [Indexed: 01/29/2023] Open
Abstract
The first rate-limiting step to successfully translate prevention of psychosis in to clinical practice is to establish specialised Clinical High Risk for Psychosis (CHR-P) services. This study systematises the knowledge regarding CHR-P services and provides guidelines for translational implementation. We conducted a PRISMA/MOOSE-compliant (PROSPERO-CRD42020163640) systematic review of Web of Science to identify studies until 4/05/2020 reporting on CHR-P service configuration, outreach strategy and referrals, service user characteristics, interventions, and outcomes. Fifty-six studies (1998-2020) were included, encompassing 51 distinct CHR-P services across 15 countries and a catchment area of 17,252,666 people. Most services (80.4%) consisted of integrated multidisciplinary teams taking care of CHR-P and other patients. Outreach encompassed active (up to 97.6%) or passive (up to 63.4%) approaches: referrals came mostly (90%) from healthcare agencies. CHR-P individuals were more frequently males (57.2%). Most (70.6%) services accepted individuals aged 12-35 years, typically assessed with the CAARMS/SIPS (83.7%). Baseline comorbid mental conditions were reported in two-third (69.5%) of cases, and unemployment in one third (36.6%). Most services provided up to 2-years (72.4%), of clinical monitoring (100%), psychoeducation (81.1%), psychosocial support (73%), family interventions (73%), individual (67.6%) and group (18.9%) psychotherapy, physical health interventions (37.8%), antipsychotics (87.1%), antidepressants (74.2%), anxiolytics (51.6%), and mood stabilisers (38.7%). Outcomes were more frequently ascertained clinically (93.0%) and included: persistence of symptoms/comorbidities (67.4%), transition to psychosis (53.5%), and functional status (48.8%). We provide ten practical recommendations for implementation of CHR-P services. Health service knowledge summarised by the current study will facilitate translational efforts for implementation of CHR-P services worldwide.
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Affiliation(s)
- Gonzalo Salazar de Pablo
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid, Spain
| | - Andrés Estradé
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Clinical and Health Psychology, Catholic University, Montevideo, Uruguay
| | - Marcello Cutroni
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Olivier Andlauer
- Heads UP Service, East London NHS Foundation Trust, London, UK
- Centre for Psychiatry, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
- National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK.
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12
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Lim K, Lam M, Huang H, Liu J, Lee J. Genetic liability in individuals at ultra-high risk of psychosis: A comparison study of 9 psychiatric traits. PLoS One 2020; 15:e0243104. [PMID: 33264322 PMCID: PMC7710117 DOI: 10.1371/journal.pone.0243104] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 11/14/2020] [Indexed: 11/19/2022] Open
Abstract
Individuals at ultra-high risk (UHR) of psychosis are characterised by the emergence of attenuated psychotic symptoms and deterioration in functioning. In view of the high non-psychotic comorbidity and low rates of transition to psychosis, the specificity of the UHR status has been called into question. This study aims to (i) investigate if the UHR construct is associated with the genetic liability of schizophrenia or other psychiatric conditions; (ii) examine the ability of polygenic risk scores (PRS) to discriminate healthy controls from UHR, remission and conversion status. PRS was calculated for 210 youths (nUHR = 102, nControl = 108) recruited as part of the Longitudinal Youth at Risk Study (LYRIKS) using nine psychiatric traits derived from twelve large-scale psychiatric genome-wide association studies as discovery datasets. PRS was also examined to discriminate UHR-Healthy control status, and healthy controls from UHR remission and conversion status. Result indicated that schizophrenia PRS appears to best index the genetic liability of UHR, while trend level associations were observed for depression and cross-disorder PRS. Schizophrenia PRS discriminated healthy controls from UHR (R2 = 7.9%, p = 2.59 x 10-3, OR = 1.82), healthy controls from non-remitters (R2 = 8.1%, p = 4.90 x 10-4, OR = 1.90), and converters (R2 = 7.6%, p = 1.61 x 10-3, OR = 1.82), with modest predictive ability. A trend gradient increase in schizophrenia PRS was observed across categories. The association between schizophrenia PRS and UHR status supports the hypothesis that the schizophrenia polygenic liability indexes the risk for developing psychosis.
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Affiliation(s)
- Keane Lim
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore, Singapore
- Feinstein Institute of Medical Research, The Zucker Hillside Hospital, New York, New York, United States of America
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Genome Institute of Singapore, Singapore, Singapore
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
| | - Jianjun Liu
- Genome Institute of Singapore, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore, Singapore
- Department of Psychosis, Institute of Mental Health, Singapore, Singapore
- Neuroscience and Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- * E-mail:
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13
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Peh OH, Rapisarda A, Lee J. Quality of parental bonding is associated with symptom severity and functioning among individuals at ultra-high risk for psychosis. Schizophr Res 2020; 215:204-10. [PMID: 31699626 DOI: 10.1016/j.schres.2019.10.029] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Revised: 08/30/2019] [Accepted: 10/12/2019] [Indexed: 11/21/2022]
Abstract
Patients with schizophrenia tend to report having 'affectionless-controlling' mothers when the Parental Bonding Instrument (PBI) is used. However, there is limited research on the parenting styles received by individuals at ultra-high risk (UHR) for psychosis. Furthermore, previous PBI studies have suggested that a three-factor solution is more suitable than the original two-factors. This study aims to i) use a more sensitive measure of parental bonding by conducting an exploratory factor analysis (EFA), and (ii) to explore the association between parental bonding, symptom severity and functioning among the UHR. Data from 164 individuals at UHR and 510 healthy controls were collected. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Calgary Depression Scale for Schizophrenia (CDSS). Functioning was measured using the Global Assessment of Functioning (GAF) and Social and Occupational Functioning Assessment Scale (SOFAS). Confirmatory factor analyses of existing factor structures and EFA of the PBI was conducted. Pearson's correlations and regressions were used to elucidate the associations between parenting factors and assessment scales. EFAs revealed a three-factor solution: 'care', 'authoritarianism', and 'overprotection'. UHR were 1.61 times more likely to report having affectionless-controlling mothers. UHR reported significantly lower maternal and paternal care, and higher maternal and paternal overprotection. Higher paternal overprotection was significantly associated with worse symptoms and functioning. Our findings replicate previous findings among individuals at UHR in an Asian setting, and suggest that affectionless-controlling or affectionless-authoritative-overprotective styles may be a poor fit for individuals at UHR.
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14
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Abstract
Despite rapidly growing knowledge of the clinical high-risk (CHR) state for psychosis, the vast majority of case-control studies have relied on healthy volunteers as a reference point for drawing inferences about the CHR construct. Researchers have long recognized that results generated from this design are limited by significant interpretive concerns, yet little attention has been given to how these concerns affect the growing field of CHR research. We argue that overreliance on healthy controls in CHR research threatens the validity of inferences concerning group differences, hinders advances in understanding the development of psychosis, and limits clinical progress. We suggest that the combined use of healthy and help-seeking (i.e., psychiatric) controls is a necessary step for the next generation of CHR research. We then evaluate methods for help-seeking control studies, identify the available CHR studies that have used such designs, discuss select findings in this literature, and offer recommendations for research.
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Affiliation(s)
| | - James M. Gold
- Maryland Psychiatric Research Center, University of Maryland School of Medicine
| | - Vijay A. Mittal
- Department of Psychology, Northwestern University
- Department of Psychiatry, Northwestern University
- Institute for Policy Research, Northwestern University
- Medical Social Sciences, Northwestern University
- Institute for Innovations in Developmental Sciences, Northwestern University
| | - Jason Schiffman
- Department of Psychology, University of Maryland, Baltimore County
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15
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Oliver D, Radua J, Reichenberg A, Uher R, Fusar-Poli P. Psychosis Polyrisk Score (PPS) for the Detection of Individuals At-Risk and the Prediction of Their Outcomes. Front Psychiatry 2019; 10:174. [PMID: 31057431 PMCID: PMC6478670 DOI: 10.3389/fpsyt.2019.00174] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 03/11/2019] [Indexed: 12/29/2022] Open
Abstract
Primary prevention in individuals at Clinical High Risk for psychosis (CHR-P) can ameliorate the course of psychotic disorders. Further advancements of knowledge have been slowed by the standstill of the field, which is mostly attributed to its epidemiological weakness. The latter, in turn, underlies the limited identification power of at-risk individuals and the relatively modest ability of CHR-P interviews to rule-in a state of risk for psychosis. In the first part, this perspective review discusses these limitations and traces a new approach to overcome them. Theoretical concepts to support a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis are presented. The PPS hinges on recent findings indicating that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors such as: parental and sociodemographic risk factors, perinatal risk factors, later risk factors, and antecedents. In the second part of this perspective review we present a prototype of a PPS encompassing core predictors beyond genetics. The PPS prototype may be piloted in the next generation of CHR-P research and combined with genetic information to refine the detection of individuals at-risk of psychosis and the prediction of their outcomes, and ultimately advance clinical research in this field.
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Affiliation(s)
- Dominic Oliver
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom
| | - Joaquim Radua
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - Abraham Reichenberg
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Frieman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom
- Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, National Institute for Health Research, London, United Kingdom
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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16
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Matsumoto K, Katsura M, Tsujino N, Nishiyama S, Nemoto T, Katagiri N, Takahashi T, Higuchi Y, Ohmuro N, Matsuoka H, Suzuki M, Mizuno M. Federated multi-site longitudinal study of at-risk mental state for psychosis in Japan. Schizophr Res 2019; 204:343-52. [PMID: 30219604 DOI: 10.1016/j.schres.2018.09.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 09/01/2018] [Accepted: 09/01/2018] [Indexed: 11/22/2022]
Abstract
There has been recent accumulation of evidence and clinical guidance regarding the at-risk mental state (ARMS) for psychosis. However, most studies have been observational cohort and intervention studies of Western populations. To assess the validity of the ARMS concept and the transition rate to psychosis in a non-Western nation, we retrospectively combined and analyzed clinical data of individuals diagnosed with ARMS who were prospectively followed-up at three specialized clinical services for ARMS in Japan. In total, we included 309 individuals with ARMS, of whom 43 developed overt psychosis. We estimated cumulative transition rates to psychosis with the Kaplan-Meier method, obtaining rates of 12% at 12, 16% at 24, 19% at 36, and 20% at 48 months. Only two individuals reported past cannabis use. Despite several differences among the three sites, transition rates did not differ among them. Furthermore, the transition rate of children aged between 14 and 17 years did not differ from that of individuals aged 18 years or older. Regression analysis revealed that meeting the brief limited intermittent psychotic symptoms (BLIPS) criterion was associated with an increased risk of transition to psychosis, whereas genetic risk factors were not. Although antipsychotic prescription was relatively frequent in this cohort, there was no evidence supporting frequent use of antipsychotics for this population. In conclusion, our findings support the assertion that the current concept of ARMS is applicable in Japan. Development of local clinical guidelines and training for clinicians is necessary to disseminate this concept to more clinical settings.
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17
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Rekhi G, Rapisarda A, Lee J. Impact of distress related to attenuated psychotic symptoms in individuals at ultra high risk of psychosis: Findings from the Longitudinal Youth at Risk Study. Early Interv Psychiatry 2019; 13:73-78. [PMID: 28560723 DOI: 10.1111/eip.12451] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2016] [Revised: 02/08/2017] [Accepted: 03/18/2017] [Indexed: 12/21/2022]
Abstract
AIM Recent studies have highlighted that attenuated psychotic symptoms (APS) are an important source of distress in ultra high risk (UHR) individuals and that this distress is related to transition to psychosis (TTP). This study examined distress associated with APS in UHR individuals and investigated its association with TTP. METHODS The Comprehensive Assessment of At-Risk Mental State (CAARMS) was used to identify 173 UHR individuals, who were included as participants in the study. Distress related to APS was self-reported. Functioning was assessed on the Social and Occupational Functioning Assessment Scale. Associations between each of the 4 APS subscales in the CAARMS-non-bizarre ideas (NBI), perceptual abnormalities (PA), unusual thought content (UTC) and disorganized speech (DS)-with its distress level were examined. RESULTS Of the 173 UHR participants, 154 (89%) reported distress related to one or more APS. NBI was rated to be the most distressing out of the 4 APS by the highest number of participants (32.9%) compared to UTC (12.1%), PA (24.9%) and DS (2.9%). Mean distress scores were significantly associated with CAARMS composite scores (P < .001). However, there was no significant relationship between distress scores and functioning. Both mean distress scores (OR = 1.034, P = .029) and functioning (OR = 0.892, P = .022) were significant predictors of transition to psychosis at 1 year of follow-up. CONCLUSIONS This study provides additional evidence to link subjective distress experienced by UHR individuals to APS and to their subsequent clinical outcomes and has significant clinical implications.
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Affiliation(s)
- Gurpreet Rekhi
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health, Singapore, Singapore.,Neuroscience & Behavioral Disorders, Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore, Singapore.,Department of General Psychiatry 1, Institute of Mental Health, Singapore, Singapore.,Office of Clinical Sciences, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
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18
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Yang Z, Lim K, Lam M, Keefe R, Lee J. Factor structure of the positive and negative syndrome scale (PANSS) in people at ultra high risk (UHR) for psychosis. Schizophr Res 2018; 201:85-90. [PMID: 29804925 DOI: 10.1016/j.schres.2018.05.024] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 03/29/2018] [Accepted: 05/13/2018] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The Positive and Negative Syndrome Scale (PANSS), a comprehensive psychopathology assessment scale used in the evaluation of psychopathology in schizophrenia, is also often used in the Ultra-High-Risk (UHR) population. This paper examined the dimensional structure of the PANSS in a UHR sample. METHODS A total of 168 individuals assessed to be at UHR for psychosis on the Comprehensive Assessment of At-Risk Mental States (CAARMS) were evaluated on the PANSS, Calgary Depression Scale for Schizophrenia (CDSS), Beck Anxiety Inventory (BAI), Brief Assessment of Cognition in Schizophrenia (BACS), and Global Assessment of Functioning (GAF). Exploratory factor analysis (EFA) of the PANSS was performed to identify the factorial structure. Convergent validity was explored with the CAARMS, CDSS, BAI and BACS. RESULTS EFA of the PANSS yielded five symptom factors - Positive, Negative, Cognition/Disorganization, Anxiety/Depression, and Hostility. This 5-factor solution showed good convergent validity with the CAARMS composite score, CDSS, BAI, and BACS. Positive, Negative and Anxiety/Depression factors were associated with functioning. CONCLUSION The reported PANSS factor structure may serve to improve the understanding and measurement of clinical symptom dimensions manifested in people with UHR for future research and clinical setting.
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Affiliation(s)
- Zixu Yang
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Keane Lim
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Max Lam
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Richard Keefe
- Department of Psychiatry & Behavioral Sciences, Duke University Medical Center, Durham, USA
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore, Singapore; Department of Psychosis, Institute of Mental Health, Singapore, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
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19
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Deriu V, Moro MR, Benoit L. Early intervention for everyone? A review of cross-cultural issues and their treatment in ultra-high-risk (UHR) cohorts. Early Interv Psychiatry 2018; 12:796-810. [PMID: 29708310 DOI: 10.1111/eip.12671] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 02/06/2018] [Accepted: 03/13/2018] [Indexed: 12/15/2022]
Abstract
AIM Over the past 20 years, early management of psychosis has become both a research and policy priority. In Western countries, psychotic disorders appear more prevalent in migrant and minority ethnic groups than in native or dominant groups. Moreover, disparities exist in health conditions and access to care among immigrants and minority ethnic groups, compared with native-born and majority groups. Appropriate early detection tools are necessary for the different groups. METHODS This systematic review provides a synthesis of the assessment and discussion of transcultural issues in ultra-high-risk (UHR) cohorts. The Medline database was searched via PubMed for peer-reviewed articles published in English from 1995 to 2017. All 79 studies included are prospective UHR cohort studies that used the Comprehensive Assessment of At-Risk Mental States (CAARMS). RESULTS In UHR cohort studies that used the CAARMS, transcultural data (native language, ethnicity, place of birth, migration) are rarely collected, and inadequate ability to speak the dominant language is a common exclusion criterion. When they are included, the CAARMS scores differ between some minorities and the native-born majority group. CONCLUSIONS This systematic review demonstrates barriers to the access to participation in early intervention research for migrants and ethnic minorities. This selection bias may result in lower validity for the CAARMS among these populations and thus in inadequate intervention programmes. Along with targeted studies, minorities' access to participation in UHR cohorts should be improved through 3 tools: interpreters at recruitment and for administration of CAARMS, a guide to cultural formulation and transcultural data collection.
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Affiliation(s)
| | - Marie Rose Moro
- Head of department at Maison de Solenn, Hôpital Cochin (AP-HP), Paris, France.,Professor of Child and Adolescent Psychiatry, Faculty of Medicine, Université Paris Descartes, Paris, France
| | - Laelia Benoit
- Maison de Solenn, Hôpital Cochin (AP-HP), Unité INSERM/CESP, Paris, France
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Lam M, Lee J, Rapisarda A, See YM, Yang Z, Lee SA, Abdul-Rashid NA, Kraus M, Subramaniam M, Chong SA, Keefe RSE. Longitudinal Cognitive Changes in Young Individuals at Ultrahigh Risk for Psychosis. JAMA Psychiatry 2018; 75:929-939. [PMID: 30046827 PMCID: PMC6142925 DOI: 10.1001/jamapsychiatry.2018.1668] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
IMPORTANCE Cognitive deficits are a key feature of risk for psychosis. Longitudinal changes in cognitive architecture may be associated with the social and occupational functioning in young people. OBJECTIVES To examine longitudinal profiles of cognition in individuals at ultrahigh risk (UHR) for psychosis, compared with healthy controls, and to investigate the association of cognition with functioning. DESIGN, SETTING, AND PARTICIPANTS This study has a multiple-group prospective design completed in 24 months and was conducted from January 1, 2009, to November 11, 2012, as part of the Longitudinal Youth at-Risk Study conducted in Singapore. Participants either were recruited from psychiatric outpatient clinics, educational institutions, and community mental health agencies or self-referred. Follow-up assessments were performed every 6 months for 2 years or until conversion to psychosis. Individuals with medical causes for psychosis, current illicit substance use, or color blindness were excluded. Data analysis was conducted from June 2014 to May 2018. MAIN OUTCOMES AND MEASURES Neuropsychological, perceptual, and social cognitive tasks; semi-structured interviews, and the Structured Clinical Interview for DSM-IV Axis I disorders were administered every 6 months. The UHR status of nonconverters, converters, remitters, and nonremitters was monitored. Cognitive domain scores and functioning were investigated longitudinally. RESULTS In total, 384 healthy controls and 173 UHR individuals between ages 14 and 29 years were evaluated prospectively. Of the 384 healthy controls, 153 (39.8%) were female and 231 (60.2%) were male with a mean (SD) age of 21.69 (3.26) years. Of the 173 individuals at UHR for psychosis, 56 (32.4%) were female and 117 (67.6%) were male with a mean (SD) age of 21.27 (3.52) years). After 24 months of follow-up, 383 healthy controls (99.7%) and 122 individuals at UHR for psychosis (70.5%) remained. Baseline cognitive deficits were associated with psychosis conversion later (mean odds ratio [OR], 1.66; combined 95% CI, 1.08-2.83; P = .04) and nonremission of UHR status (mean OR, 1.67; combined 95% CI, 1.09-2.95; P = .04). Five cognitive components-social cognition, attention, verbal fluency, general cognitive function, and perception-were obtained from principal components analysis. Longitudinal component structure change was observed in general cognitive function (maximum vertical deviation = 0.59; χ2 = 8.03; P = .01). Group-by-time interaction on general cognitive function (F = 12.23; η2 = 0.047; P < .001) and perception (F = 8.33; η2 = 0.032; P < .001) was present. Changes in attention (F = 5.65; η2 = 0.013; P = .02) and general cognitive function (F = 7.18; η2 = 0.014; P = .01) accounted for longitudinal changes in social and occupational functioning. CONCLUSIONS AND RELEVANCE Individuals in this study who met the UHR criteria appeared to demonstrate cognitive deficits, and those whose UHR status remitted were seen to recover cognitively. Cognition appeared as poor in nonremitters and appeared to be associated with poor functional outcome. This study suggests that cognitive dimensions are sensitive to the identification of young individuals at risk for psychosis and to the longitudinal course of those at highest risk.
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Affiliation(s)
- Max Lam
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health,
Singapore, Singapore,Department of General Psychiatry 1, Institute of
Mental Health, Singapore, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health,
Singapore, Singapore,Neuroscience and Behavioural Disorders, Duke-NUS
Medical School, Singapore, Singapore
| | - Yuen Mei See
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Zixu Yang
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Sara-Ann Lee
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | | | - Michael Kraus
- Department of Psychiatry and Behavioral Sciences, Duke
University Medical Center, Durham, North Carolina
| | | | - Siow-Ann Chong
- Research Division, Institute of Mental Health,
Singapore, Singapore
| | - Richard S. E. Keefe
- Department of Psychiatry and Behavioral Sciences, Duke
University Medical Center, Durham, North Carolina
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21
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Yee JY, Lee TS, Lee J. Levels of Serum Brain-Derived Neurotropic Factor in Individuals at Ultra-High Risk for Psychosis-Findings from the Longitudinal Youth at Risk Study (LYRIKS). Int J Neuropsychopharmacol 2018; 21:734-739. [PMID: 29584866 PMCID: PMC6070044 DOI: 10.1093/ijnp/pyy036] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 03/11/2018] [Accepted: 03/23/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Identifying biomarkers to enrich prognostication and risk predictions in individuals at high risk of developing psychosis will enable stratified early intervention efforts. Brain-derived neurotrophic factor has been widely studied in schizophrenia and in first-episode psychosis with promising results. The aim of this study was to examine the levels of serum brain-derived neurotrophic factor between healthy controls and individuals with ultra-high risk of psychosis. METHODS A sample of 106 healthy controls and 105 ultra-high risk of psychosis individuals from the Longitudinal Youth at Risk Study was included in this study. Ultra-high risk of psychosis status was determined using the Comprehensive Assessment of At-Risk Mental State at recruitment. Calgary Depression Scale for Schizophrenia was used to assess the severity of depression. All participants were followed up for 2 years, and ultra-high risk of psychosis remitters were defined by ultra-high risk of psychosis individuals who no longer fulfilled Comprehensive Assessment of At-Risk Mental State criteria at the end of the study period. Levels of brain-derived neurotrophic factor were measured in the serum by enzyme-linked immunosorbent assay method. RESULTS The ultra-high risk of psychosis group had significantly higher baseline levels of serum brain-derived neurotrophic factor compared with the control group (3.7 vs 3.3 ng/mL, P=.018). However, baseline levels of serum brain-derived neurotrophic factor did not predict the development of psychosis (OR=0.64, CI=0.40-1.02) or remission (OR=0.83, CI=0.60-1.15) from ultra-high risk of psychosis status. CONCLUSION Findings from our study did not support a role for serum brain-derived neurotrophic factor in predicting outcomes in ultra-high risk of psychosis individuals. However, the finding of higher levels of serum brain-derived neurotrophic factor in ultra-high risk of psychosis individuals deserves further study.
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Affiliation(s)
- Jie Yin Yee
- Research Division, Institute of Mental Health, Singapore,Correspondence: Jie Yin Yee, MSc, Institute of Mental Health 10 Buangkok View, Singapore 539747 ()
| | - Tih-Shih Lee
- Neuroscience & Behavioural Disorders, Duke-NUS Medical School, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore,North Region & Department of Psychosis, Institute of Mental Health, Singapore,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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22
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Oliver D, Kotlicka-Antczak M, Minichino A, Spada G, McGuire P, Fusar-Poli P. Meta-analytical prognostic accuracy of the Comprehensive Assessment of at Risk Mental States (CAARMS): The need for refined prediction. Eur Psychiatry 2018; 49:62-68. [PMID: 29413807 DOI: 10.1016/j.eurpsy.2017.10.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 10/04/2017] [Accepted: 10/04/2017] [Indexed: 10/18/2022] Open
Abstract
Primary indicated prevention is reliant on accurate tools to predict the onset of psychosis. The gold standard assessment for detecting individuals at clinical high risk (CHR-P) for psychosis in the UK and many other countries is the Comprehensive Assessment for At Risk Mental States (CAARMS). While the prognostic accuracy of CHR-P instruments has been assessed in general, this is the first study to specifically analyse that of the CAARMS. As such, the CAARMS was used as the index test, with the reference index being psychosis onset within 2 years. Six independent studies were analysed using MIDAS (STATA 14), with a total of 1876 help-seeking subjects referred to high risk services (CHR-P+: n=892; CHR-P-: n=984). Area under the curve (AUC), summary receiver operating characteristic curves (SROC), quality assessment, likelihood ratios, and probability modified plots were computed, along with sensitivity analyses and meta-regressions. The current meta-analysis confirmed that the 2-year prognostic accuracy of the CAARMS is only acceptable (AUC=0.79 95% CI: 0.75-0.83) and not outstanding as previously reported. In particular, specificity was poor. Sensitivity of the CAARMS is inferior compared to the SIPS, while specificity is comparably low. However, due to the difficulties in performing these types of studies, power in this meta-analysis was low. These results indicate that refining and improving the prognostic accuracy of the CAARMS should be the mainstream area of research for the next era. Avenues of prediction improvement are critically discussed and presented to better benefit patients and improve outcomes of first episode psychosis.
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Affiliation(s)
- D Oliver
- Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom.
| | - M Kotlicka-Antczak
- Medical University of Lodz, Department of Affective and Psychotic Disorders, Lodz, Poland
| | - A Minichino
- Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - G Spada
- Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom
| | - P McGuire
- Department of Psychosis Studies, IoPPN, King's College London, London SE5 8AF, United Kingdom; OASIS Service, South London and the Maudsley NHS National Health Service Foundation Trust, London, United Kingdom; National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health, IoPPN, King's College London, SE5 8AF, United Kingdom
| | - P Fusar-Poli
- Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom; OASIS Service, South London and the Maudsley NHS National Health Service Foundation Trust, London, United Kingdom; National Institute for Health Research (NIHR) Biomedical Research Centre for Mental Health, IoPPN, King's College London, SE5 8AF, United Kingdom
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23
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Lee TY, Lee J, Kim M, Choe E, Kwon JS. Can We Predict Psychosis Outside the Clinical High-Risk State? A Systematic Review of Non-Psychotic Risk Syndromes for Mental Disorders. Schizophr Bull 2018; 44:276-285. [PMID: 29438561 PMCID: PMC5814842 DOI: 10.1093/schbul/sbx173] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Recent evidence has suggested that psychosis could develop not only in people at clinical high risk for psychosis (CHR-P) but also in those with clinical risk syndromes for emergent nonpsychotic mental disorders. The proportion of people with these clinical risk syndromes who will develop psychosis rather than to other nonpsychotic mental disorders is undetermined. Electronic databases were searched for studies reporting on clinical risk syndromes for the development of emergent nonpsychotic mental disorders. Incidence of emerging psychotic and nonpsychotic mental disorders defined on the ICD or DSM. Of a total of 9 studies relating to 3006 nonpsychotic at-risk individuals were included. Within prospective studies (n = 4, sample = 1051), the pooled incidence of new psychotic disorders across these clinical risk syndromes was of 12.9 per 1000 person-years (95% CI: 4.3 to 38.6) and that of nonpsychotic disorders (n = 3, sample = 538) was of 43.5 per 1000 person-years (95% CI: 30.9 to 61.3). Psychotic disorders may emerge outside the CHR-P paradigm, from clinical risk syndromes for incident nonpsychotic disorders, albeit at lower rates than in the CHR-P group. The clinical risk syndromes for emerging nonpsychotic disorders may exhibit a pluripotential risk of developing several types of mental disorders compared with CHR-P. If substantiated by future research, the current findings suggest that it may be useful to move beyond the current strategy of identifying individuals meeting CHR-P criteria only.
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Affiliation(s)
- Tae Young Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Junhee Lee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Minah Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eugenie Choe
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea,Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea,To whom correspondence should be addressed; Department of Psychiatry, Seoul National University College of Medicine, 101 Daehak-no, Chongno-gu, Seoul 03035, Republic of Korea; e-mail:
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24
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Chan CT, Abdin E, Subramaniam M, Tay SA, Lim LK, Verma S. Two-Year Clinical and Functional Outcomes of an Asian Cohort at Ultra-High Risk of Psychosis. Front Psychiatry 2018; 9:758. [PMID: 30761027 PMCID: PMC6362403 DOI: 10.3389/fpsyt.2018.00758] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 12/20/2018] [Indexed: 11/13/2022] Open
Abstract
Background: To determine the 2-year clinical and functional outcomes of an Asian cohort at ultra-high risk (UHR) of psychosis. Method: This was a longitudinal study with a follow-up period of 2 years on 255 help-seeking adolescents and young adults at UHR of psychosis managed by a multi-disciplinary mental health team in Singapore. Clients received case management, psychosocial, and pharmacological treatment as appropriate. Data comprising symptom and functional outcomes were collected over the observation period by trained clinicians and psychiatrists. Results: The 2-year psychosis transition rate was 16.9%, with a median time to transition of 168 days. After 2 years, 14.5% of the subjects had persistent at-risk symptoms while 7.5% developed other non-psychotic psychiatric disorders. 38.4% of the cohort had recovered and was discharged from mental health services. The entire cohort's functioning improved as reflected by an increase in the score of the Social and Occupational Functioning Assessment Scale during the follow-up period. Predictors to psychosis transition included low education level, baseline unemployment, a history of violence, and brief limited intermittent psychotic symptoms, while male gender predicted the persistence of UHR state, or the development of non-psychotic disorders. Conclusion: Use of the current UHR criteria allows us to identify individuals who are at imminent risk of developing not just psychosis, but also those who may develop other mental health disorders. Future research should include identifying the needs of those who do not transition to psychosis, while continuing to refine on ways to improve the UHR prediction algorithm for psychosis.
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Affiliation(s)
- Chun Ting Chan
- Institute of Mental Health, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore
| | | | | | | | - Lay Keow Lim
- Institute of Mental Health, Singapore, Singapore
| | - Swapna Verma
- Institute of Mental Health, Singapore, Singapore.,Duke-NUS Medical School, Singapore, Singapore
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25
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Goh WWB, Sng JCG, Yee JY, See YM, Lee TS, Wong L, Lee J. Can Peripheral Blood-Derived Gene Expressions Characterize Individuals at Ultra-high Risk for Psychosis? Comput Psychiatr 2017; 1:168-183. [PMID: 30090857 PMCID: PMC6067827 DOI: 10.1162/cpsy_a_00007] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Accepted: 06/07/2017] [Indexed: 12/17/2022]
Abstract
The ultra-high risk (UHR) state was originally conceived to identify individuals at imminent risk of developing psychosis. Although recent studies have suggested that most individuals designated UHR do not, they constitute a distinctive group, exhibiting cognitive and functional impairments alongside multiple psychiatric morbidities. UHR characterization using molecular markers may improve understanding, provide novel insight into pathophysiology, and perhaps improve psychosis prediction reliability. Whole-blood gene expressions from 56 UHR subjects and 28 healthy controls are checked for existence of a consistent gene expression profile (signature) underlying UHR, across a variety of normalization and heterogeneity-removal techniques, including simple log-conversion, quantile normalization, gene fuzzy scoring (GFS), and surrogate variable analysis. During functional analysis, consistent and reproducible identification of important genes depends largely on how data are normalized. Normalization techniques that address sample heterogeneity are superior. The best performer, the unsupervised GFS, produced a strong and concise 12-gene signature, enriched for psychosis-associated genes. Importantly, when applied on random subsets of data, classifiers built with GFS are "meaningful" in the sense that the classifier models built using genes selected after other forms of normalization do not outperform random ones, but GFS-derived classifiers do. Data normalization can present highly disparate interpretations on biological data. Comparative analysis has shown that GFS is efficient at preserving signals while eliminating noise. Using this, we demonstrate confidently that the UHR designation is well correlated with a distinct blood-based gene signature.
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Affiliation(s)
- Wilson Wen Bin Goh
- School of Biological Sciences, Nanyang Technological University, Singapore
- Department of Computer Science, National University of Singapore, Singapore
| | - Judy Chia-Ghee Sng
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jie Yin Yee
- Research Division, Institute of Mental Health, Singapore
| | - Yuen Mei See
- Research Division, Institute of Mental Health, Singapore
| | - Tih-Shih Lee
- Neuroscience and Behavioral Disorders Program, Duke–National University of Singapore Medical School, Singapore
| | - Limsoon Wong
- Department of Computer Science, National University of Singapore, Singapore
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
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26
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Lam M, Wang M, Huang W, Eng GK, Rapisarda A, Kraus M, Kang S, Keefe RSE, Lee J. Establishing the Brief Assessment of Cognition - Short form. J Psychiatr Res 2017; 93:1-11. [PMID: 28549241 DOI: 10.1016/j.jpsychires.2017.05.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 04/30/2017] [Accepted: 05/15/2017] [Indexed: 10/19/2022]
Abstract
The study aims to identify and validate a parsimonious subset of tests in the commonly used Brief Assessment of Cognition in Schizophrenia (BACS) that allows the evaluation of global cognitive ability. Several permutations of subtests from the BACS were examined to identify the best subset of tests to compose the short form measure. The Brief Assessment of Cognition-Short Form (BAC-SF) was evaluated for convergent validity in healthy and psychiatric samples (N = 3718). Verbal Memory, Digit Sequencing, and Symbol Coding subtests were found to best summarize the variance of composite scores in both Asian and US Norming samples (r = 0.91) indicating that BAC-SF is an appropriate approximation of cognitive deficits. Test re-test reliability of the BAC-SF was adequate (Intraclass Correlation Coefficient (ICC) = 0.73) and showed sufficient separation between healthy controls and schizophrenia (Average Predictive Accuracy = 79.9%; replication = 76.5%). Findings indicate that the BAC-SF an could be used as a cognitive screener for large-scale clinical and epidemiological studies. The short form does not replace the need for comprehensive neuropsychological batteries purposed for detailed neuropsychological and clinical investigation of cognitive function. Further replication of the construct might be necessary in other clinical populations.
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Affiliation(s)
- Max Lam
- Research Division, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore.
| | - Mingyuan Wang
- Research Division, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore
| | - Wanping Huang
- Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, 308433, Singapore
| | - Goi Khia Eng
- Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore
| | - Michael Kraus
- Psychiatry and Behavioral Sciences, 8 Duke University Medical Center Greenspace, Durham, NC 27703, USA
| | - Sim Kang
- Research Division, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore; General Psychiatry, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore
| | - R S E Keefe
- Psychiatry and Behavioral Sciences, 8 Duke University Medical Center Greenspace, Durham, NC 27703, USA
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore; General Psychiatry, Institute of Mental Health, Buangkok Green Medical Park 10 Buangkok View, 539747, Singapore
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27
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Abstract
Attenuated psychotic symptoms (APS) are the key criteria to identify the individuals at enhanced risk of developing psychotic disorders. Competing clinicians-rated or self-rated psychometric instruments can also be used to detect APS, which makes it difficult to interpret their actual clinical significance. This article summarizes the empirical differences between the clinicians-rated and self-rated interviews and explores the impact of the context (referral pathways, settings, and assessment procedures) on the clinical significance of the APS.
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Affiliation(s)
- Paolo Fusar-Poli
- King's College London, Institute of Psychiatry Psychology and Neuroscience, PO63, De Crespigny Park, SE5 8AF London, UK
- OASIS Service, South London And the Maudsley NHS Foundation Trust, London, UK
| | - Andrea Raballo
- Norwegian Centre for Mental Disorders Research (NORMENT), University of Oslo, Oslo, Norway
| | - Josef Parnas
- Department of Clinical Medicine, Region Hovedstadens Psykiatri, Brøndby, Denmark
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28
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Ho NF, Holt DJ, Cheung M, Iglesias JE, Goh A, Wang M, Lim JK, de Souza J, Poh JS, See YM, Adcock AR, Wood SJ, Chee MW, Lee J, Zhou J. Progressive Decline in Hippocampal CA1 Volume in Individuals at Ultra-High-Risk for Psychosis Who Do Not Remit: Findings from the Longitudinal Youth at Risk Study. Neuropsychopharmacology 2017; 42:1361-70. [PMID: 28079061 DOI: 10.1038/npp.2017.5] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 12/05/2016] [Accepted: 01/04/2017] [Indexed: 01/08/2023]
Abstract
Most individuals identified as ultra-high-risk (UHR) for psychosis do not develop frank psychosis. They continue to exhibit subthreshold symptoms, or go on to fully remit. Prior work has shown that the volume of CA1, a subfield of the hippocampus, is selectively reduced in the early stages of schizophrenia. Here we aimed to determine whether patterns of volume change of CA1 are different in UHR individuals who do or do not achieve symptomatic remission. Structural MRI scans were acquired at baseline and at 1-2 follow-up time points (at 12-month intervals) from 147 UHR and healthy control subjects. An automated method (based on an ex vivo atlas of ultra-high-resolution hippocampal tissue) was used to delineate the hippocampal subfields. Over time, a greater decline in bilateral CA1 subfield volumes was found in the subgroup of UHR subjects whose subthreshold symptoms persisted (n=40) and also those who developed clinical psychosis (n=12), compared with UHR subjects who remitted (n=41) and healthy controls (n=54). No baseline differences in volumes of the overall hippocampus or its subfields were found among the groups. Moreover, the rate of volume decline of CA1, but not of other hippocampal subfields, in the non-remitters was associated with increasing symptom severity over time. Thus, these findings indicate that there is deterioration of CA1 volume in persistently symptomatic UHR individuals in proportion to symptomatic progression.
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29
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Abstract
The Clinical High-Risk state for psychosis (CHR-P) paradigm was introduced about 2 decades ago. Over this period of time accumulating knowledge has been gained. Conceptual advancements involve new knowledge into risk enrichment and the impact of recruitment strategies, specificity for prediction of psychotic and nonpsychotic mental disorders and heterogeneity of psychosis risk among the different CHR-P subgroups. The current special issue advances current knowledge on deconstructing the CHR-P paradigm across its 3 subgroups: genetic risk, attenuated psychotic symptoms, and short-lived and remitting psychotic episodes. A conceptual revision of the paradigm (Version II) is suggested and supported by 3 original studies published in this special issue.
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Affiliation(s)
- Paolo Fusar-Poli
- Department of Psychosis Studies, Institute of Psychiatry , Psychology and Neuroscience, King's College London, London, UK;
- OASIS Service, South London and the Maudsley NHS Foundation Trust, London, UK
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30
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Conrad AM, Lewin TJ, Sly KA, Schall U, Halpin SA, Hunter M, Carr VJ. Utility of risk-status for predicting psychosis and related outcomes: evaluation of a 10-year cohort of presenters to a specialised early psychosis community mental health service. Psychiatry Res 2017; 247:336-344. [PMID: 27984822 DOI: 10.1016/j.psychres.2016.12.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2016] [Revised: 11/21/2016] [Accepted: 12/03/2016] [Indexed: 01/13/2023]
Abstract
Psychosis transition rates by those at clinical high risk have been highly variable and few studies have compared service presenters across the full psychosis risk spectrum with respect to medium-term outcomes. A 10-year service cohort was examined (N=1997), comprising all presentations to an early psychosis service for young people experiencing a recent psychotic episode or at increased risk ('Psychological Assistance Service', Newcastle, Australia). Baseline and longitudinal service data (median follow-up =7.3 years) were used in a series of logistic regressions to examine relationships between psychosis risk-status and subsequent illness episodes, hospital admissions, and community contacts. Six baseline groups were identified: existing (14.5%) and recent psychosis (19.8%); ultra-high risk (UHR, 9.6%); non-psychotic disorders without (35.4%, the reference group) and with psychiatric admissions (8.3%); and incomplete assessments (12.5%). High comorbidity levels were reported by the cohort (psychosocial problems, 61.1%; depression, 54.1%; substance misuse, 40.7%). UHR clients experienced similar psychosis transition rates to the reference group (17.3% vs. 14.6%; 8.9% vs. 9.1% within 2-years) and comparable rates of subsequent non-psychosis outcomes. A 25.9% conversion rate from early psychosis to schizophrenia was detected. However, among transitioning individuals, UHR clients faired relatively better, particularly with respect to changes in comorbidity and mental health contacts. Interventions tailored to current problems, recovery and psychological strengthening may be more appropriate than those based on estimated psychosis risk, which currently lacks clinical utility.
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Affiliation(s)
- Agatha M Conrad
- Centre for Brain and Mental Health Research (CBMHR), Hunter New England Mental Health, the University of Newcastle, and Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia.
| | - Terry J Lewin
- Centre for Brain and Mental Health Research (CBMHR), Hunter New England Mental Health, the University of Newcastle, and Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia; Schizophrenia Research Institute, Neuroscience Research Australia, Randwick, NSW, Australia.
| | - Ketrina A Sly
- Centre for Brain and Mental Health Research (CBMHR), Hunter New England Mental Health, the University of Newcastle, and Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia
| | - Ulrich Schall
- Centre for Brain and Mental Health Research (CBMHR), Hunter New England Mental Health, the University of Newcastle, and Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia; Schizophrenia Research Institute, Neuroscience Research Australia, Randwick, NSW, Australia; Child and Adolescent Mental Health Services, Hunter New England Mental Health, Newcastle, NSW, Australia
| | - Sean A Halpin
- Centre for Brain and Mental Health Research (CBMHR), Hunter New England Mental Health, the University of Newcastle, and Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia; Child and Adolescent Mental Health Services, Hunter New England Mental Health, Newcastle, NSW, Australia; School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, Australia
| | - Mick Hunter
- Centre for Brain and Mental Health Research (CBMHR), Hunter New England Mental Health, the University of Newcastle, and Hunter Medical Research Institute (HMRI), Newcastle, NSW, Australia; School of Psychology, University of Newcastle, University Drive, Callaghan, NSW, Australia
| | - Vaughan J Carr
- Schizophrenia Research Institute, Neuroscience Research Australia, Randwick, NSW, Australia; School of Psychiatry, University of New South Wales, Kensington, NSW, Australia; Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
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Fusar-Poli P, Rutigliano G, Stahl D, Davies C, De Micheli A, Ramella-Cravaro V, Bonoldi I, McGuire P. Long-term validity of the At Risk Mental State (ARMS) for predicting psychotic and non-psychotic mental disorders. Eur Psychiatry 2017; 42:49-54. [PMID: 28212505 DOI: 10.1016/j.eurpsy.2016.11.010] [Citation(s) in RCA: 89] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 11/18/2016] [Accepted: 11/21/2016] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND The long-term clinical validity of the At Risk Mental State (ARMS) for the prediction of non-psychotic mental disorders is unknown. METHODS Clinical register-based cohort study including all non-psychotic individuals assessed by the Outreach And Support in South London (OASIS) service (2002-2015). The primary outcome was risk of developing any mental disorder (psychotic or non-psychotic). Analyses included Cox proportional hazard models, Kaplan-Meier survival/failure function and C statistics. RESULTS A total of 710 subjects were included. A total of 411 subjects were at risk (ARMS+) and 299 not at risk (ARMS-). Relative to ARMS-, the ARMS+ was associated with an increased risk (HR=4.825) of developing psychotic disorders, and a reduced risk (HR=0.545) of developing non-psychotic disorders (mainly personality disorders). At 6-year, the ARMS designation retained high sensitivity (0.873) but only modest specificity (0.456) for the prediction of psychosis onset (AUC 0.68). The brief and limited intermittent psychotic symptoms (BLIPS) subgroup had a higher risk of developing psychosis, and a lower risk of developing non-psychotic disorders as compared to the attenuated psychotic symptoms (APS) subgroup (P<0.001). CONCLUSIONS In the long-term, the ARMS specifically predicts the onset of psychotic disorders, with modest accuracy, but not of non-psychotic disorders. Individuals meeting BLIPS criteria have distinct clinical outcomes. SIGNIFICANT OUTCOMES In the long-term, the ARMS designation is still significantly associated with an increased risk of developing psychotic disorders but its prognostic accuracy is only modest. There is no evidence that the ARMS is associated with an increased risk of developing non-psychotic mental disorders. The BLIPS subgroup at lower risk of developing non-psychotic disorders compared to the APS subgroup. LIMITATIONS While incident diagnoses employed in this study are high in ecological validity they have not been subjected to formal validation with research-based criteria.
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Kraus M, Rapisarda A, Lam M, Thong JYJ, Lee J, Subramaniam M, Collinson SL, Chong SA, Keefe RSE. Disrupted latent inhibition in individuals at ultra high-risk for developing psychosis. Schizophr Res Cogn 2016; 6:1-8. [PMID: 28740818 PMCID: PMC5514297 DOI: 10.1016/j.scog.2016.07.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Revised: 07/22/2016] [Accepted: 07/23/2016] [Indexed: 11/29/2022]
Abstract
The addition of off-the-shelf cognitive measures to established prodromal criteria has resulted in limited improvement in the prediction of conversion to psychosis. Tests that assess cognitive processes central to schizophrenia might better identify those at highest risk. The latent inhibition paradigm assesses a subject's tendency to ignore irrelevant stimuli, a process integral to healthy perceptual and cognitive function that has been hypothesized to be a key deficit underlying the development of schizophrenia. In this study, 142 young people at ultra high-risk for developing psychosis and 105 controls were tested on a within-subject latent inhibition paradigm. Additionally, we later inquired about the strategy that each subject employed to complete the test, and further investigated the relationship between reported strategy and the extent of latent inhibition exhibited. Unlike controls, ultra high-risk subjects did not demonstrate a significant latent inhibition effect. This difference between groups became greater when controlling for strategy. The lack of latent inhibition effect in our ultra high-risk sample suggests that individuals at ultra high-risk for psychosis are impaired in their allocation of attentional resources based on past predictive value of repeated stimuli. This fundamental deficit in the allocation of attention may contribute to the broader array of cognitive impairments and clinical symptoms displayed by individuals at ultra high-risk for psychosis.
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Affiliation(s)
- Michael Kraus
- Department of Psychiatry & Behavioral Sciences, Duke University Medical Center, 200 Trent Drive, Durham, NC, 27710
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747.,Neuroscience & Behavioral Disorders, Duke-National University of Singapore, Graduate Medical School, 8 College Road, Singapore, 169857
| | - Max Lam
- Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747
| | - Jamie Y J Thong
- Department of Bioengineering, National University of Singapore, Block E4, #04-08, 4 Engineering Drive 3, Singapore, 117583
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747.,Department of General Psychiatry 1, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747.,Office of Clinical Sciences, Duke-National University of Singapore, Graduate Medical School, National University of Singapore, 8 College Road, Singapore, 169857
| | - Mythily Subramaniam
- Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747
| | - Simon L Collinson
- Neuroscience & Behavioral Disorders, Duke-National University of Singapore, Graduate Medical School, 8 College Road, Singapore, 169857
| | - Siow Ann Chong
- Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747
| | - Richard S E Keefe
- Department of Psychiatry & Behavioral Sciences, Duke University Medical Center, 200 Trent Drive, Durham, NC, 27710.,Neuroscience & Behavioral Disorders, Duke-National University of Singapore, Graduate Medical School, 8 College Road, Singapore, 169857
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Fusar-Poli P, Schultze-Lutter F, Cappucciati M, Rutigliano G, Bonoldi I, Stahl D, Borgwardt S, Riecher-Rössler A, Addington J, Perkins DO, Woods SW, McGlashan T, Lee J, Klosterkötter J, Yung AR, McGuire P. The Dark Side of the Moon: Meta-analytical Impact of Recruitment Strategies on Risk Enrichment in the Clinical High Risk State for Psychosis. Schizophr Bull 2016; 42:732-43. [PMID: 26591006 PMCID: PMC4838090 DOI: 10.1093/schbul/sbv162] [Citation(s) in RCA: 157] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND The individual risk of developing psychosis after being tested for clinical high-risk (CHR) criteria (posttest risk of psychosis) depends on the underlying risk of the disease of the population from which the person is selected (pretest risk of psychosis), and thus on recruitment strategies. Yet, the impact of recruitment strategies on pretest risk of psychosis is unknown. METHODS Meta-analysis of the pretest risk of psychosis in help-seeking patients selected to undergo CHR assessment: total transitions to psychosis over the pool of patients assessed for potential risk and deemed at risk (CHR+) or not at risk (CHR-). Recruitment strategies (number of outreach activities per study, main target of outreach campaign, and proportion of self-referrals) were the moderators examined in meta-regressions. RESULTS 11 independent studies met the inclusion criteria, for a total of 2519 (CHR+: n = 1359; CHR-: n = 1160) help-seeking patients undergoing CHR assessment (mean follow-up: 38 months). The overall meta-analytical pretest risk for psychosis in help-seeking patients was 15%, with high heterogeneity (95% CI: 9%-24%, I (2) = 96, P < .001). Recruitment strategies were heterogeneous and opportunistic. Heterogeneity was largely explained by intensive (n = 11, β = -.166, Q = 9.441, P = .002) outreach campaigns primarily targeting the general public (n = 11, β = -1.15, Q = 21.35, P < .001) along with higher proportions of self-referrals (n = 10, β = -.029, Q = 4.262, P = .039), which diluted pretest risk for psychosis in patients undergoing CHR assessment. CONCLUSIONS There is meta-analytical evidence for overall risk enrichment (pretest risk for psychosis at 38 monhts = 15%) in help-seeking samples selected for CHR assessment as compared to the general population (pretest risk of psychosis at 38 monhts=0.1%). Intensive outreach campaigns predominantly targeting the general population and a higher proportion of self-referrals diluted the pretest risk for psychosis.
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Affiliation(s)
| | - Frauke Schultze-Lutter
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, Department of Child and Adolescent Psychiatry, University of Bern, Bern, Switzerland
| | - Marco Cappucciati
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Grazia Rutigliano
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | | | - Daniel Stahl
- Department of Biostatistics, Institute of Psychiatry Psychology and Neuroscience, King's College London, London UK
| | - Stephan Borgwardt
- Department of Psychiatry (UPK), University of Basel Psychiatric Clinics, Basel, Switzerland
| | - Anita Riecher-Rössler
- Department of Psychiatry (UPK), University of Basel Psychiatric Clinics, Basel, Switzerland
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT
| | | | - Jimmy Lee
- Department of General Psychiatry, Institute of Mental Health, Singapore, Singapore
| | | | - Alison R Yung
- Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - Philip McGuire
- Department of Psychosis Studies, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, UK
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Lam M, Abdul Rashid NA, Lee SA, Lim J, Foussias G, Fervaha G, Ruhrman S, Remington G, Lee J. Baseline social amotivation predicts 1-year functioning in UHR subjects: A validation and prospective investigation. Eur Neuropsychopharmacol 2015; 25:2187-96. [PMID: 26553972 DOI: 10.1016/j.euroneuro.2015.10.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Revised: 08/17/2015] [Accepted: 10/22/2015] [Indexed: 12/15/2022]
Abstract
Social amotivation and diminished expression have been reported to underlie negative symptomatology in schizophrenia. In the current study we sought to establish and validate these negative symptom domains in a large cohort of schizophrenia subjects (n=887) and individuals who are deemed to be Ultra-High Risk (UHR) for psychosis. Confirmatory factor analysis conducted on PANSS item domains demonstrate that the dual negative symptom domains exist in schizophrenia and UHR subjects. We further sought to examine if these negative symptom domains were associated with functioning in UHR subjects. Linear regression analyses confirmed that social amotivation predicted functioning in UHR subjects prospectively at 1 year follow up. Results suggest that the association between social amotivation and functioning is generalisable beyond schizophrenia populations to those who are at-risk of developing psychosis. Social amotivation may be an important dimensional clinical construct to be studied across a range of psychiatric conditions.
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Affiliation(s)
- Max Lam
- Research Division, Institute of Mental Health, Singapore, Singapore
| | | | - Sara-Ann Lee
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - Jeanette Lim
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - George Foussias
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada
| | - Gagan Fervaha
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Canada
| | - Stephan Ruhrman
- Department of Psychiatry and Psychotherapy, University of Cologne, Germany
| | - Gary Remington
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Canada; Institute of Medical Science, University of Toronto, Canada; Department of Psychiatry, University of Toronto, Canada
| | - Jimmy Lee
- Research Division, Institute of Mental Health, Singapore, Singapore; Department of General Psychiatry 1, Institute of Mental Health, Singapore, Singapore; Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore, Singapore.
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Klauser P, Zhou J, Lim JK, Poh JS, Zheng H, Tng HY, Krishnan R, Lee J, Keefe RS, Adcock RA, Wood SJ, Fornito A, Chee MW. Lack of Evidence for Regional Brain Volume or Cortical Thickness Abnormalities in Youths at Clinical High Risk for Psychosis: Findings From the Longitudinal Youth at Risk Study. Schizophr Bull 2015; 41:1285-93. [PMID: 25745033 PMCID: PMC4601700 DOI: 10.1093/schbul/sbv012] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
There is cumulative evidence that young people in an "at-risk mental state" (ARMS) for psychosis show structural brain abnormalities in frontolimbic areas, comparable to, but less extensive than those reported in established schizophrenia. However, most available data come from ARMS samples from Australia, Europe, and North America while large studies from other populations are missing. We conducted a structural brain magnetic resonance imaging study from a relatively large sample of 69 ARMS individuals and 32 matched healthy controls (HC) recruited from Singapore as part of the Longitudinal Youth At-Risk Study (LYRIKS). We used 2 complementary approaches: a voxel-based morphometry and a surface-based morphometry analysis to extract regional gray and white matter volumes (GMV and WMV) and cortical thickness (CT). At the whole-brain level, we did not find any statistically significant difference between ARMS and HC groups concerning total GMV and WMV or regional GMV, WMV, and CT. The additional comparison of 2 regions of interest, hippocampal, and ventricular volumes, did not return any significant difference either. Several characteristics of the LYRIKS sample like Asian origins or the absence of current illicit drug use could explain, alone or in conjunction, the negative findings and suggest that there may be no dramatic volumetric or CT abnormalities in ARMS.
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Affiliation(s)
- Paul Klauser
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, Australia;,Monash Clinical and Imaging Neuroscience, School of Psychological Sciences & Monash Biomedical Imaging, Monash University, Clayton, Australia;,These authors contributed equally to the article
| | - Juan Zhou
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore;
| | - Joseph K.W. Lim
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Joann S. Poh
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Hui Zheng
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Han Ying Tng
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Ranga Krishnan
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Jimmy Lee
- Department of General Psychiatry 1 and Research Division, Institute of Mental Health, Singapore, Singapore;,Office of Clinical Sciences, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Richard S.E. Keefe
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC
| | - R. Alison Adcock
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC;,Center for Cognitive Neuroscience, Duke University, Durham, NC
| | - Stephen J. Wood
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, Australia;,School of Psychology, University of Birmingham, Edgbaston, UK
| | - Alex Fornito
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Melbourne, Australia;,Monash Clinical and Imaging Neuroscience, School of Psychological Sciences & Monash Biomedical Imaging, Monash University, Clayton, Australia
| | - Michael W.L. Chee
- Center for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
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Fusar-Poli P, Cappucciati M, Rutigliano G, Schultze-Lutter F, Bonoldi I, Borgwardt S, Riecher-Rössler A, Addington J, Perkins D, Woods SW, McGlashan TH, Lee J, Klosterkötter J, Yung AR, McGuire P. At risk or not at risk? A meta-analysis of the prognostic accuracy of psychometric interviews for psychosis prediction. World Psychiatry 2015; 14:322-32. [PMID: 26407788 PMCID: PMC4592655 DOI: 10.1002/wps.20250] [Citation(s) in RCA: 181] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR-). The reference index was psychosis onset over time in both CHR+ and CHR- subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR+: N=1,359; CHR-: N=1,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.
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Affiliation(s)
- Paolo Fusar-Poli
- King's College London, Institute of Psychiatry, London, UK
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
| | | | | | - Frauke Schultze-Lutter
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Ilaria Bonoldi
- King's College London, Institute of Psychiatry, London, UK
| | | | | | - Jean Addington
- Hotchkiss Brain Institute, Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Diana Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | | | - Jimmy Lee
- Department of General Psychiatry, Institute of Mental Health, Singapore, Singapore
| | | | - Alison R Yung
- Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK
| | - Philip McGuire
- King's College London, Institute of Psychiatry, London, UK
- OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK
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Lim J, Rekhi G, Rapisarda A, Lam M, Kraus M, Keefe RSE, Lee J. Impact of psychiatric comorbidity in individuals at Ultra High Risk of psychosis - Findings from the Longitudinal Youth at Risk Study (LYRIKS). Schizophr Res 2015; 164:8-14. [PMID: 25818728 DOI: 10.1016/j.schres.2015.03.007] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Revised: 03/09/2015] [Accepted: 03/09/2015] [Indexed: 12/19/2022]
Abstract
Recent studies have reported a high prevalence of psychiatric comorbidities in Ultra High Risk (UHR) for psychosis populations. This study examined the prevalence of comorbidity and its impact on symptoms, functioning, cognition and transition to psychosis in the Longitudinal Youth at Risk Study (LYRIKS) sample. The Comprehensive Assessment of At-Risk Mental State (CAARMS) was used to identify UHR individuals and 163 participants were included in the study. Comorbid disorders were identified using the Structured Clinical Interview for DSM-IV-TR Axis I Disorders. Participants were evaluated on the CAARMS, Positive and Negative Syndrome Scale, Calgary Depression Scale for Schizophrenia, Beck Anxiety Inventory, Global Assessment of Functioning and Brief Assessment of Cognition in Schizophrenia. Clinical, functioning and cognitive characteristics by lifetime and current comorbidity groups were compared using multivariate tests. Independent predictors of comorbidity were identified through logistic regression. Chi-squared tests were used to compare comorbidity rates between those who had developed psychosis at one year and those who had not. We found that 131 UHR participants (80.4%) had a lifetime comorbidity while 82 (50.3%) had a current comorbidity with depressive disorders being the most common. UHR individuals with comorbidity had more severe symptoms, higher distress and lower functioning with no differences in general cognition. Lower functioning was associated with current comorbidity. Eleven participants (6.7%) had developed psychosis after one year and there were no differences in the comorbidity rates between those who developed psychosis and those who did not. Psychiatric comorbidities in the UHR group are associated with adverse clinical outcomes and warrant closer attention.
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Affiliation(s)
- Jeanette Lim
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore 539747, Singapore
| | - Gurpreet Rekhi
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore 539747, Singapore
| | - Attilio Rapisarda
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore 539747, Singapore; Neuroscience & Behavioral Disorders, Duke-NUS Graduate Medical School, 8 College Road, Singapore 169857, Singapore
| | - Max Lam
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore 539747, Singapore
| | - Michael Kraus
- Department of Psychiatry & Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
| | - Richard S E Keefe
- Neuroscience & Behavioral Disorders, Duke-NUS Graduate Medical School, 8 College Road, Singapore 169857, Singapore; Department of Psychiatry & Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
| | - Jimmy Lee
- Research Division, Institute of Mental Health, 10 Buangkok View, Singapore 539747, Singapore; Department of General Psychiatry 1, Institute of Mental Health, 10 Buangkok View, Singapore 539747, Singapore; Office of Clinical Sciences, Duke-NUS Graduate Medical School, 8 College Road, Singapore 169857, Singapore.
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38
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Schultze-Lutter F, Michel C, Schmidt SJ, Schimmelmann BG, Maric NP, Salokangas RKR, Riecher-Rössler A, van der Gaag M, Nordentoft M, Raballo A, Meneghelli A, Marshall M, Morrison A, Ruhrmann S, Klosterkötter J. EPA guidance on the early detection of clinical high risk states of psychoses. Eur Psychiatry 2015; 30:405-16. [PMID: 25735810 DOI: 10.1016/j.eurpsy.2015.01.010] [Citation(s) in RCA: 237] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Revised: 01/29/2015] [Accepted: 01/29/2015] [Indexed: 01/15/2023] Open
Abstract
The aim of this guidance paper of the European Psychiatric Association is to provide evidence-based recommendations on the early detection of a clinical high risk (CHR) for psychosis in patients with mental problems. To this aim, we conducted a meta-analysis of studies reporting on conversion rates to psychosis in non-overlapping samples meeting any at least any one of the main CHR criteria: ultra-high risk (UHR) and/or basic symptoms criteria. Further, effects of potential moderators (different UHR criteria definitions, single UHR criteria and age) on conversion rates were examined. Conversion rates in the identified 42 samples with altogether more than 4000 CHR patients who had mainly been identified by UHR criteria and/or the basic symptom criterion 'cognitive disturbances' (COGDIS) showed considerable heterogeneity. While UHR criteria and COGDIS were related to similar conversion rates until 2-year follow-up, conversion rates of COGDIS were significantly higher thereafter. Differences in onset and frequency requirements of symptomatic UHR criteria or in their different consideration of functional decline, substance use and co-morbidity did not seem to impact on conversion rates. The 'genetic risk and functional decline' UHR criterion was rarely met and only showed an insignificant pooled sample effect. However, age significantly affected UHR conversion rates with lower rates in children and adolescents. Although more research into potential sources of heterogeneity in conversion rates is needed to facilitate improvement of CHR criteria, six evidence-based recommendations for an early detection of psychosis were developed as a basis for the EPA guidance on early intervention in CHR states.
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Affiliation(s)
- F Schultze-Lutter
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - C Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - S J Schmidt
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - B G Schimmelmann
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - N P Maric
- School of Medicine, University of Belgrade and Clinic of Psychiatry, Clinical Center of Serbia, Belgrade, Serbia
| | | | - A Riecher-Rössler
- Center for Gender Research and Early Detection, Psychiatric University Clinics Basel, Basel, Switzerland
| | - M van der Gaag
- Department of Clinical Psychology, VU University and EMGO Institute for Health and Care Research, Amsterdam, The Netherlands; Psychosis Research, Parnassia Psychiatric Institute, The Hague, The Netherlands
| | - M Nordentoft
- Mental Health Center Copenhagen, University of Copenhagen, Copenhagen, Denmark
| | - A Raballo
- Department of Mental Health, Reggio Emilia Public Health Centre, Reggio Emilia, Italy; Regional Working Group on Early Detection of Psychosis, Emilia Romagna Regional Health Service, Bologna, Italy
| | - A Meneghelli
- Dipartimento di Salute Mentale, Centro per l'Individuazione e l'Intervento Precoce nelle Psicosi-Programma 2000, Ospedale Niguarda Ca' Granda, Milan, Italy
| | - M Marshall
- School of Medicine, University of Manchester, Manchester, UK; LANTERN Centre, Lancashire Care NHS Foundation Trust, Preston, UK
| | - A Morrison
- School of Psychological Sciences, University of Manchester, Manchester, UK; Psychosis Research Unit, Greater Manchester West NHS Mental Health Trust, Manchester, UK
| | - S Ruhrmann
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - J Klosterkötter
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany.
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